



from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

lowercase_										=  [
    """python""",
    """tqdm""",
    """regex""",
    """requests""",
    """packaging""",
    """filelock""",
    """numpy""",
    """tokenizers""",
    """huggingface-hub""",
    """safetensors""",
    """accelerate""",
    """pyyaml""",
]

for pkg in pkgs_to_check_at_runtime:
							if pkg in deps:
														if pkg == "tokenizers":
																					# must be loaded here, or else tqdm check may fail
																					from .utils import is_tokenizers_available

																					if not is_tokenizers_available():
																												continue  # not required, check version only if installed
														elif pkg == "accelerate":
																					# must be loaded here, or else tqdm check may fail
																					from .utils import is_accelerate_available

																					# Maybe switch to is_torch_available in the future here so that Accelerate is hard dep of
																					# Transformers with PyTorch
																					if not is_accelerate_available():
																												continue  # not required, check version only if installed

														require_version_core(deps[pkg])
							else:
														raise ValueError(F'can\'t find {pkg} in {deps.keys()}, check dependency_versions_table.py')



def __lowerCAmelCase			(  SCREAMING_SNAKE_CASE_    ,	SCREAMING_SNAKE_CASE_=None	):
			require_version(deps[pkg]    ,	a__	)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCamelCase__  =					{
    '''configuration_longformer''': [
        '''LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''LongformerConfig''',
        '''LongformerOnnxConfig''',
    ],
    '''tokenization_longformer''': ['''LongformerTokenizer'''],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					['''LongformerTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					[
       '''LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''LongformerForMaskedLM''',
       '''LongformerForMultipleChoice''',
       '''LongformerForQuestionAnswering''',
       '''LongformerForSequenceClassification''',
       '''LongformerForTokenClassification''',
       '''LongformerModel''',
       '''LongformerPreTrainedModel''',
       '''LongformerSelfAttention''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__  =					[
       '''TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFLongformerForMaskedLM''',
       '''TFLongformerForMultipleChoice''',
       '''TFLongformerForQuestionAnswering''',
       '''TFLongformerForSequenceClassification''',
       '''TFLongformerForTokenClassification''',
       '''TFLongformerModel''',
       '''TFLongformerPreTrainedModel''',
       '''TFLongformerSelfAttention''',
   ]


if TYPE_CHECKING:
   from .configuration_longformer import (
       LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       LongformerConfig,
       LongformerOnnxConfig,
   )
   from .tokenization_longformer import LongformerTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_longformer_fast import LongformerTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_longformer import (
          LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          LongformerForMaskedLM,
          LongformerForMultipleChoice,
          LongformerForQuestionAnswering,
          LongformerForSequenceClassification,
          LongformerForTokenClassification,
          LongformerModel,
          LongformerPreTrainedModel,
          LongformerSelfAttention,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_longformer import (
          TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFLongformerForMaskedLM,
          TFLongformerForMultipleChoice,
          TFLongformerForQuestionAnswering,
          TFLongformerForSequenceClassification,
          TFLongformerForTokenClassification,
          TFLongformerModel,
          TFLongformerPreTrainedModel,
          TFLongformerSelfAttention,
      )

else:
   import sys

   lowerCamelCase__  =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




